cap: Covariate Assisted Principal (CAP) Regression for Covariance Matrix Outcomes

Performs Covariate Assisted Principal (CAP) Regression for covariance matrix outcomes. The method identifies the optimal projection direction which maximizes the log-likelihood function of the log-linear heteroscedastic regression model in the projection space. See Zhao et al. (2018), Covariate Assisted Principal Regression for Covariance Matrix Outcomes, <doi:10.1101/425033> for details.

Version: 1.0
Depends: MASS, multigroup
Published: 2018-09-30
Author: Yi Zhao, Bingkai Wang, Stewart Mostofsky, Brian Caffo, Xi Luo
Maintainer: Yi Zhao <zhaoyi1026 at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: cap results

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Reference manual: cap.pdf
Package source: cap_1.0.tar.gz
Windows binaries: r-devel: cap_1.0.zip, r-release: cap_1.0.zip, r-oldrel: cap_1.0.zip
OS X binaries: r-release: cap_1.0.tgz, r-oldrel: cap_1.0.tgz

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